DESCRIPTION: Autoimmune uveitis (AU) is a heterogeneous group of diseases with unknown cause, characterized by inflammation in the uveal track in the eye that may lead to loss of vision. Identification of AU-associated autoantigens would markedly improve our understanding of the disease etiology and facilitate the diagnosis and treatment. Although a handful of autoantigens have been identified in animals, it is not known whether these proteins are antigenic targets in humans, how many other autoantigens are yet to be identified and how patient genetic background may influence autoantigen profile. Acute anterior uveitis (AAU) is a clinically distinct entity with approximately half of AAU patients HLA-B27 positive. The hypothesis for this study is that B27+ and B27- AAU patients share some autoantigens common to inflammation-susceptible tissues in the eye, but differ in others. Autoantibodies in patient serum can be used as molecular probes to identify autoantigens by various methods. However, most available techniques are of low sensitivity and efficiency and have not been productive. To investigate the hypothesis, a novel system of subtractive phage display has been developed to identify patient autoantigens, which can be independently verified for binding affinity, patient specificity, immunogenicity and disease relevance. The hypothesis will be investigated with the following aims: 1) To identify autoantigens from B27+ and B27- AAU patients by phage display and to verify the binding affinity and patient specificity of the autoantigens by various antibody-based analyses;2) To delineate the role of T cells in AAU-associated autoimmunity and to independently validate the immunogenicity of the autoantigens;3) To define the disease relevance of the autoantigens by statistic comparison of the patients and controls and to correlate the B and T cell responses with the clinical course and severity of AAU. The proposed work capitalizes on a new means of identifying autoantigens that is unbiased, sensitive and efficient. Identified autoantigens will be independently validated without relying on animal models and their complicated cross-species interpretation. This study will also lead to development of autoantigen array, a powerful tool that will allow us to profile hundreds of autoantigens efficiently for individual patients. These efforts will advance our understanding of the disease etiology and prognosis, and improve the diagnosis and therapy.